Paper

{
  "abstract": "The dominant sequence transduction models are based on complex recurrent or convolutional neural networks that include an encoder and a decoder. … We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely.",
  "authors": [
    "Ashish Vaswani",
    "Noam Shazeer",
    "Niki Parmar",
    "Jakob Uszkoreit",
    "Llion Jones",
    "Aidan N. Gomez",
    "Lukasz Kaiser",
    "Illia Polosukhin"
  ],
  "citation": {
    "apa": "Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017). Attention Is All You Need. Advances in Neural Information Processing Systems. https://doi.org/10.48550/arxiv.1706.03762",
    "bibtex": "@article{vaswani2017attention,\n  title={Attention Is All You Need},\n  author={Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N. and Kaiser, Lukasz and Polosukhin, Illia},\n  journal={Advances in Neural Information Processing Systems},\n  year={2017},\n  doi={10.48550/arxiv.1706.03762}\n}"
  },
  "citationCount": 181057,
  "citationsPerYear": 18105.7,
  "coverage": {
    "complete": true,
    "missing": [],
    "retry": false
  },
  "doi": "10.48550/arxiv.1706.03762",
  "id": "10.48550/arxiv.1706.03762",
  "is_retracted": false,
  "oa_status": "green",
  "pdfUrl": "https://arxiv.org/pdf/1706.03762",
  "title": "Attention Is All You Need",
  "tldr": "A new simple network architecture, the Transformer, based solely on attention mechanisms, is proposed and shown to be superior in quality while being more parallelizable and requiring significantly less time to train.",
  "type": "preprint",
  "url": "https://doi.org/10.48550/arxiv.1706.03762",
  "venue": "Advances in Neural Information Processing Systems",
  "year": 2017
}

# bash or zsh: see the payment challenge. Nothing is charged.
curl -sS -g -i 'https://papers.use.x402atlas.com/paper?id=10.48550%2Farxiv.1706.03762'

# x402 v2 sends the challenge base64-encoded in the PAYMENT-REQUIRED header (v1 sends it in the body).
# To read the header:
curl -sS -g -o /dev/null -D - 'https://papers.use.x402atlas.com/paper?id=10.48550%2Farxiv.1706.03762' \
  | grep -i '^payment-required:' | cut -d' ' -f2 | tr -d '\r' | base64 --decode

// npm i @x402/fetch @x402/evm viem
import { wrapFetchWithPayment, x402Client } from "@x402/fetch";
import { registerExactEvmScheme } from "@x402/evm/exact/client";
import { privateKeyToAccount } from "viem/accounts";

// Pays at most $0.005 per call.
const client = new x402Client().setSpendControls({ maxAmountPerPayment: "$0.005" });
registerExactEvmScheme(client, { signer: privateKeyToAccount(process.env.EVM_PRIVATE_KEY) });
const pay = wrapFetchWithPayment(fetch, client);

// Not sure it's safe to pay? ToolVet checks it first for $0.005. Pay for that from a separate
// client: this one is capped at $0.005 per payment. GET https://toolvet.app/api/v1/check?url=https%3A%2F%2Fpapers.use.x402atlas.com%2Fpaper
const res = await pay("https://papers.use.x402atlas.com/paper?id=10.48550%2Farxiv.1706.03762");
console.log(res.status, await res.text());

# pip install "x402[requests,evm]"
import os
from eth_account import Account
from x402 import x402ClientSync
from x402.http.clients import x402_requests
from x402.mechanisms.evm import EthAccountSigner
from x402.mechanisms.evm.exact.register import register_exact_evm_client

# Pays at most $0.005 per call.
client = x402ClientSync().set_spend_controls({"max_amount_per_payment": "$0.005"})
register_exact_evm_client(client, EthAccountSigner(Account.from_key(os.environ["EVM_PRIVATE_KEY"])))

with x402_requests(client) as session:
    res = session.get("https://papers.use.x402atlas.com/paper?id=10.48550%2Farxiv.1706.03762")
    print(res.status_code, res.text)